| // |
| // Copyright © 2023 Arm Ltd and Contributors. All rights reserved. |
| // SPDX-License-Identifier: MIT |
| // |
| |
| #include <OpaqueDelegateUtils.hpp> |
| |
| #include <tensorflow/lite/builtin_ops.h> |
| #include <tensorflow/lite/c/builtin_op_data.h> |
| #include <tensorflow/lite/c/common.h> |
| #include <tensorflow/lite/minimal_logging.h> |
| |
| namespace armnnOpaqueDelegate |
| { |
| TfLiteStatus VisitArgMinMaxOperator(DelegateData& delegateData, |
| TfLiteOpaqueContext* tfLiteContext, |
| TfLiteOpaqueNode* tfLiteNode, |
| int nodeIndex, |
| int32_t argMinMaxOperatorCode) |
| { |
| TF_LITE_ENSURE_STATUS(ValidateNumInputs(tfLiteContext, tfLiteNode, 2, nodeIndex)); |
| TF_LITE_ENSURE_STATUS(ValidateNumOutputs(tfLiteContext, tfLiteNode, 1, nodeIndex)); |
| |
| // Gather input indices and use to get input tensor. |
| auto numInputs = TfLiteOpaqueNodeNumberOfInputs(tfLiteNode); |
| const int* inputTensors; |
| if (TfLiteOpaqueNodeInputs(tfLiteNode, &inputTensors, &numInputs) != kTfLiteOk) |
| { |
| TF_LITE_OPAQUE_MAYBE_KERNEL_LOG( |
| tfLiteContext, |
| "TfLiteArmnnOpaqueDelegate: Unable to gather input tensor indices from node #%d: ", |
| nodeIndex); |
| return kTfLiteError; |
| } |
| |
| const TfLiteOpaqueTensor* tfLiteInputTensor = TfLiteOpaqueContextGetOpaqueTensor(tfLiteContext, inputTensors[0]); |
| if (!IsValid(tfLiteContext, tfLiteInputTensor, argMinMaxOperatorCode, nodeIndex)) |
| { |
| return kTfLiteError; |
| } |
| |
| // Use input indices to get filter tensor. |
| const TfLiteOpaqueTensor* tfLiteAxisTensor = TfLiteOpaqueContextGetOpaqueTensor(tfLiteContext, inputTensors[1]); |
| if(!IsValid(tfLiteAxisTensor)) |
| { |
| TF_LITE_OPAQUE_MAYBE_KERNEL_LOG( |
| tfLiteContext, |
| "TfLiteArmnnOpaqueDelegate: Invalid filter tensor in operator #%d node #%d: ", |
| argMinMaxOperatorCode, nodeIndex); |
| return kTfLiteError; |
| } |
| |
| // Gather output indices and use to get output tensors. |
| int numOutputs = 0; |
| const int* outputTensors; |
| if (TfLiteOpaqueNodeOutputs(tfLiteNode, &outputTensors, &numOutputs) != kTfLiteOk) |
| { |
| TF_LITE_OPAQUE_MAYBE_KERNEL_LOG( |
| tfLiteContext, |
| "TfLiteArmnnOpaqueDelegate: Unable to gather output tensor indices from node #%d: ", |
| nodeIndex); |
| return kTfLiteError; |
| } |
| |
| const TfLiteOpaqueTensor* tfLiteOutputTensor = TfLiteOpaqueContextGetOpaqueTensor(tfLiteContext, outputTensors[0]); |
| if (!IsValid(tfLiteContext, tfLiteOutputTensor, argMinMaxOperatorCode, nodeIndex)) |
| { |
| return kTfLiteError; |
| } |
| |
| const armnn::TensorInfo& inputTensorInfo = GetTensorInfoForTfLiteOpaqueTensor(tfLiteInputTensor); |
| const armnn::TensorInfo& outputTensorInfo = GetTensorInfoForTfLiteOpaqueTensor(tfLiteOutputTensor, true); |
| |
| // Get const axis value from model and set it to descriptor. |
| if (!IsValid(tfLiteContext, tfLiteAxisTensor, argMinMaxOperatorCode, nodeIndex)) |
| { |
| return kTfLiteError; |
| } |
| |
| armnn::ArgMinMaxDescriptor desc; |
| auto* axisData = static_cast<int*>(TfLiteOpaqueTensorData(tfLiteAxisTensor)); |
| // Get the axis value from the input tensor |
| switch (TfLiteOpaqueTensorType(tfLiteAxisTensor)) |
| { |
| case kTfLiteInt32: |
| case kTfLiteInt64: |
| desc.m_Axis = axisData[0]; |
| break; |
| default: |
| TF_LITE_OPAQUE_MAYBE_KERNEL_LOG( |
| tfLiteContext, |
| "TfLiteArmnnOpaqueDelegate: Axis value data type is not supported in operator #%d node #%d: ", |
| argMinMaxOperatorCode, nodeIndex); |
| return kTfLiteError; |
| } |
| |
| // If output_type is int32 then set Signed32 else Signed64. Default type is Signed64. |
| if (argMinMaxOperatorCode == kTfLiteBuiltinArgMax) |
| { |
| desc.m_Function = armnn::ArgMinMaxFunction::Max; |
| auto* argMaxParameters = reinterpret_cast<TfLiteArgMaxParams*>(TfLiteOpaqueNodeGetBuiltinData(tfLiteNode)); |
| if (argMaxParameters->output_type != kTfLiteInt32 && argMaxParameters->output_type != kTfLiteInt64) |
| { |
| TF_LITE_OPAQUE_MAYBE_KERNEL_LOG( |
| tfLiteContext, |
| "TfLiteArmnnOpaqueDelegate: output_type data type is not supported in operator #%d node #%d: ", |
| argMinMaxOperatorCode, nodeIndex); |
| return kTfLiteError; |
| } |
| } |
| else |
| { |
| desc.m_Function = armnn::ArgMinMaxFunction::Min; |
| auto* argMinParameters = reinterpret_cast<TfLiteArgMinParams*>(TfLiteOpaqueNodeGetBuiltinData(tfLiteNode)); |
| if (argMinParameters->output_type != kTfLiteInt32 && argMinParameters->output_type != kTfLiteInt64) |
| { |
| TF_LITE_OPAQUE_MAYBE_KERNEL_LOG( |
| tfLiteContext, |
| "TfLiteArmnnOpaqueDelegate: output_type data type is not supported in operator #%d node #%d: ", |
| argMinMaxOperatorCode, nodeIndex); |
| return kTfLiteError; |
| } |
| } |
| |
| bool isSupported = false; |
| armnn::BackendId setBackend; |
| auto validateFunc = [&](const armnn::TensorInfo& outInfo, bool& isSupported) |
| { |
| FORWARD_LAYER_OPAQUE_SUPPORT_FUNC("ARGMINMAX", |
| tfLiteContext, |
| IsArgMinMaxSupported, |
| delegateData.m_Backends, |
| isSupported, |
| setBackend, |
| inputTensorInfo, |
| outInfo, |
| desc); |
| }; |
| |
| if (!delegateData.m_Network) |
| { |
| validateFunc(outputTensorInfo, isSupported); |
| return isSupported ? kTfLiteOk : kTfLiteError; |
| } |
| |
| // Add an ArgMinMax layer |
| armnn::IConnectableLayer* layer = delegateData.m_Network->AddArgMinMaxLayer(desc); |
| layer->SetBackendId(setBackend); |
| ARMNN_ASSERT(layer != nullptr); |
| |
| armnn::IOutputSlot& outputSlot = layer->GetOutputSlot(0); |
| outputSlot.SetTensorInfo(outputTensorInfo); |
| |
| // try to connect the Constant Inputs if there are any |
| if(ProcessInputs(layer,delegateData, tfLiteContext, tfLiteNode) != kTfLiteOk ) |
| { |
| return kTfLiteError; |
| } |
| |
| // Connect |
| return Connect(layer, tfLiteContext, tfLiteNode, delegateData); |
| } |
| |
| } |